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Predict Rental Enquiries and Fraud Detection using Log Loss Method in Python

In this project, we will predict the number of inquiries a new listing receives based on the listing's creation date and other features.
4.54.5

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What will you learn

  • Featuring rental listing data
  • Real Estate data understanding
  • Better handle fraud control
  • Identify potential listing quality issues
  • Prediction Model Building
  • Evaluation using log loss method

What will you get

  • Access to recording of the complete project
  • Access to all material related to project like data files, solution files etc.

Project Description

Finding the perfect place to call your new home should be more than browsing through endless listings. RentHop makes apartment search smarter by using data to sort rental listings by quality. But while looking for the perfect apartment is difficult enough, structuring and making sense of all available real estate data programmatically is even harder.

Two Sigma invites you to apply your talents in this recruiting competition featuring rental listing data from RentHop. We will predict the number of inquiries a new listing receives based on the listing’s creation date and other features. Doing so will help RentHop better handle fraud control, identify potential listing quality issues, and allow owners and agents to better understand renters’ needs and preferences.

Instructors

 
Shaik

Data Scientist / Business Consultant at GE

3 years of rich working experience in BIG Data, Business Intelligence & Analytics with CMMI Level 5 Organizations in BFSI, Manufacturing Sector. Excellent written and oral communications, strong analytical and problem solving capabilities. Constantly learning and experimenting emerging open source tools and technologie see more...